Experience: 3+ years of experience in AI/ML engineering, with exposure to both classical machine learning methods and language model-based applications
Technical Skills: Advanced proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; expertise with Transformer architectures; hands-on experience with LangChain or similar LLM frameworks; experience with designing end-to-end RAG systems using state of the art orchestration frameworks (hands on experience with fine-tuning LLMs for specific tasks and use cases considered as an additional advantage)
MLOps Knowledge: Strong understanding of MLOps tools and practices, including version control, CI/CD pipelines, containerization, orchestration, Infrastructure as Code, automated deployment
Deployment: Experience in deploying LLM and other AI models with cloud platforms (AWS, Azure) and machine learning workbenches for robust and scalable productization
Practical overview and experience with AWS services to design cloud solutions, familiarity with Azure is a plus; experience with working with GenAI specific services like Azure OpenAI, Amazon Bedrock, Amazon SageMaker JumpStart, etc.
Data Engineering: Expertise in working with structured and unstructured data, including data cleaning, feature engineering with data stores like vector, relational, NoSQL databases and data lakes through APIs
Model Evaluation and Metrics: Proficiency in evaluating both classical ML models and LLMs using relevant metrics
Optimization Techniques: Experience with optimizing models for performance
Problem-Solving Skills: Strong analytical skills with the ability to tackle complex engineering challenges, integrate new technologies, and improve existing processes.
The successful candidate should also
Hold B.Sc., B.Eng., M.Sc., M.Eng., Ph.D. or D.Eng. in Computer Science or equivalent degree and experience with Artificial Intelligence
Be eager to explore and implement the latest advancements in LLMs and ML, integrating them with existing solutions and enhancing their capabilities
Be passionate about AI and stay up-to-date with the latest developments in LLMs, GenAI, and AI in general
Be team-oriented, proactive, and collaborative
Be an excellent problem solver and analytical thinker
Be a good communicator
Be detail-oriented and highly organized
Be willing to learn and expand their skill set
Have the ability to work collaboratively in a fast-paced, dynamic environment